This dissertation investigates near-synchronous collaboration in programming environments by means of Conflict-free Replicated Data Types (CRDTs). While screen sharing and video conferencing offer basic features for collaborative programming, IDEembedded collaboration tools provide precise tracking of source code changes and developer control. CRDTs enable decentralized collaboration, eliminating central server dependencies. However, existing CRDTs fail to preserve user intent and handle complex formats, leading to inefficiencies. Using a Design Science Research approach, this dissertation addresses four key research areas: (1) Identifying the limitations of existing CRDT algorithms in preserving user intent for programming files, (2) Optimizing CRDT implementations for programming collaboration requirements, (3) Determining the appropriate granularity for replicated data types in programming environments, (4) Exploring supervised imitation learning to enhance system capabilities in merging conflicts. This work aims to improve collaborative programming tools, ensuring higher consistency, efficiency, and user satisfaction.